基于公交优先通行的交叉口相位设计方法研究

交叉口公交优先是公交优先发展的一个重要措施,对缓解城市的交通压力和保证城市未来的可持续发展都具有重大意义。基于公交优先通行的相位设计是实施交叉口公交优先的有效措施之一,合理的相位设计将有助于求得最佳的公交优先信号控制方案。在交叉口相位设计过程中,不同流向的各股交通流的客流量可能会出现较大差异,但大多数信号设计对这种差异并不重视。本文在十字型信号控制交叉口典型相位设计基础上,对基于公交优先通行的相位设计方法进行了研究和探讨。实例分析表明:该方法在保持以pcu为单位的通行能力不变的条件下,提高以人为单位的通行能力,减少人均延误,充分体现以人为本的设计思想。     

车站有源应答器报文延迟问题情况分析

随着我国高速铁路的快速发展,列控系统得以迅速推广实施。列控中心在发送报文时,会存在多种原因的延迟,使在进路改变、点灯和轨道区段发码状态改变、临时限速改变的情况下,有源应答器报文没有更新。为此针对不同类型有源应答器的报文延迟对列车实际运行带来的影响进行分析。     

利用FDL解决光包交换中竞争冲突的研究

随着日益增长的信息量和宽带化的要求,光包交换将成为未来交换领域中最为重要的技术之一.在电交换领域或光交换领域,数据包冲突(即对同一资源的竞争)都是一个不可避免的技术问题.因此本文利用FDL建立一个光交换竞争机制以解决光包交换中的冲突,并建立数学分析模型,利用Matlab对模型进行仿真并得出结论.     

Measuring the performance of airport resilience to severe weather events

The increased severe weather events in recent years as a result of global climate change has created a substantial challenge for aviation system operation. Although transportation engineers and planners have attempted to improve system resilience through the adaptation of new technologies and the implementation of various strategies to achieve effective risk management, it remains unclear how resilience performance (measured by the speed of recovery) of airports varies in different severe weather events and what factors may explain such variations. This paper addresses these fundamental questions using the aviation system in China as an example. A resilience metric, which reflects the speed of recovery (bounce back) from a shock, was developed to measure the performance of airport resilience under various severe weather conditions. In addition, an empirical econometric analysis was conducted based on a dataset that includes both detailed aviation performance and weather conditions for the period of October 2016 – September 2017. The research findings show that airport resilience to severe weather events does vary substantially based on factors, such as weather conditions, airport capacity, and the level of modal substitution. In particular, the recovery time of air services in central and south China tends to be relatively longer in thunderstorms than other weather conditions. The study also confirms that modal substitution is a very effective resilience tactic of the transportation system as the recovery speed of air service was found to be faster by 22.9% if an alternative mode, such as high-speed rail (HSR) service was also available in the city.     

A route guidance system considering travel time unreliability

Under a stochastic roadway, drivers need a route guidance system incorporating travel time variability. To recommend a customized path depending on the trip purpose and the driver’s risk-taking behavior, various path ranking methods have been developed. Unlike those methods, our proposed disutility method can easily incorporate a target arrival time in the ranking process by measuring how late the travel is and by penalizing it depending on the severity of lateness. In addition, the disutility-based route guidance system can properly address travel time unreliability that causes unacceptable disruptions to the driver’s schedule (i.e., unexpected long delay). We compare the disutility-based path ranking method with other ranking methods, the percentile travel time, the mean excess travel time, and the on-time arrival probability. We show that the disutility has stronger discriminating power and requires less solution space to find an optimal path. The most important advantage is that it can estimate a driver’s risk-taking behavior for each trip purpose by using the discrete choice analysis. We construct a simulation framework to acquire the travel time data on a hypothetical roadway. We analyze the data and show how various ranking methods recommend a customized path. Using the data, we show the advantage of the disutiltiy method over the other methods, which is generating a customized path with respect to the target arrival time by properly penalizing the travel time lateness.     

Vehicle scheduling under stochastic trip times: An approximate dynamic programming approach

Due to unexpected demand surge and supply disruptions, road traffic conditions could exhibit substantial uncertainty, which often makes bus travelers encounter start delays of service trips and substantially degrades the performance of an urban transit system. Meanwhile, rapid advances of information and communication technologies have presented tremendous opportunities for intelligently scheduling a bus fleet. With the full consideration of delay propagation effects, this paper is devoted to formulating the stochastic dynamic vehicle scheduling problem, which dynamically schedules an urban bus fleet to tackle the trip time stochasticity, reduce the delay and minimize the total costs of a transit system. To address the challenge of “curse of dimensionality”, we adopt an approximate dynamic programming approach (ADP) where the value function is approximated through a three-layer feed-forward neural network so that we are capable of stepping forward to make decisions and solving the Bellman’s equation through sequentially solving multiple mixed integer linear programs. Numerical examples based on the realistic operations dataset of bus lines in Beijing have demonstrated that the proposed neural-network-based ADP approach not only exhibits a good learning behavior but also significantly outperforms both myopic and static polices, especially when trip time stochasticity is high.     

轨道车辆MVB通信网络的实时特性

多功能车辆总线(MVB)应用于轨道交通车辆的车厢级通信网络已经成为新一代列车通信网的发展趋势。采用MVB必须满足轨道车辆对数据传输提出的实时性要求。MVB网络的端到端传输延迟主要包括报文分组在缓存器内的平均等待延迟、发送报文分组延迟、介质传播延迟等,而影响发送报文分组延迟的主要因素是报文分组的平均等待延迟受介质访问控制方式的约束;主设备消息事件请求帧的到达过程服从泊松分布,多消息事件并发引发的事件仲裁延迟是影响消息数据报文延迟的重要因素。仿真实验结果表明,MVB网络的过程数据具有报文分组传输时间确定、报文分组长度对网络延迟影响小等实时特性,但消息数据的报文延迟受网络负载的影响较大。运用排队理论分析主从轮询方式下过程数据的延迟与MVB的轮询周期、通信速率的关系;分析数据表明,该方法可以取代以往的国外经验值来配置网络,而且配置指标更符合实际运行的要求,并已经成功应用于实际设备的测试分析中。     

公交停靠站点车辆延误研究

针对公交停靠站点的车辆延误机理进行了分析,根据停靠站点的停车次数进行分类,确定出公交停靠站点车辆延误的计算公式,并通过实例进行验证,结果与实际情况基本相符合。     

摩托车高强度螺栓延迟断裂的预防

延迟断裂是材料在静止应力作用下,经过一定时间后突然脆性破坏的一种现象,是材料、环境和应力相互作用而发生的一种环境脆化,是由氢导致材质恶化的一种形态。延迟断裂现象是妨碍高强度螺栓提高强度的一个主要因素。     

一种调度区段晚点时长的神经网络预测模型

晚点是区段内列车运行受到扰动后出现的时刻表偏移现象,为分析和预测晚点的发生,相关研究通常采用晚点传播分析、实绩数据统计的方法改善模型输出结果。在现有分析方法的基础上,设计了初始晚点和连带晚点的分类方法,将列车在调度区段的开行转化为有向图表示,并通过分析有向弧内的计划时间饱和度,实现了晚点的分类与传播路径的确定。在分类方法提供的数据基础上,提出了晚点预测模型,采用反向传播神经网络预测晚点时长。组合模型使用北京铁路局某调度区段的实际运行数据进行验证,结果表明允许误差为5 min时,神经网络的晚点时长预测准确率为85.5%,网络受突发事件影响较大,模型拟合复杂数据关系的能力需要进一步改善。